We developed multiple theories to explain chemo-mechanical complex networks involving a small number of elements, such as a general theory to predict small-number effects in catalytic reaction networks and a dynamic simulation approach to evaluate mechanical communication pathways between molecules or subunits. We also devised methods to analyze noisy data, including model-free change point analysis, error-based extraction of free-energy landscapes, and modeling with minimum excessive information that is not warranted by the data, to provide a basis to explain the individuality of molecules and cells using data science. We demonstrated the validity and applicability of these theoretical results for actual experiments in the field of “minority biology”.